This study assesses present-day extreme climate changes over China by using a set of phase 6 of the Coupled Model Intercomparison Project (CMIP6) statistical downscaled data and raw models outputs. The downscaled data is produced by the adapted spatial disaggregation and equal distance cumulative distribution function (EDCDF) method at the resolution of 0.25° × 0.25° for the present day (1961–2014) and the future period (2015–2100) under the Shared Socioeconomic Path-way (SSP) 2-4.5 than SSP5-8.5 emission scenario. The results show that the downscaling method improves the spatial distributions of extreme climate events in China with higher spatial pattern correlations, Taylor Skill Scores and closer magnitudes no matter single model or multi model ensemble (MME). In the future projections, large inter-model variability between the downscaled models still exists, particular for maximum consecutive 5-day precipitation (RX5). The downscaled MME projects that total precipitation (PTOT) and RX5, will increase with time, especially for the northwest China. The projected heavy precipitation days (R20) also increase in the future. The region of significant increase in R20 locates in the south of river Yangtze. Maxi-mum annual temperature (TXX) and percentage of warm days (TX90p) are projected to increase across the whole country with larger magnitude over the west China. Projected changes of minimum annual temperature (TNN) over the northeastern China is the most significant area. The higher of the emission scenario, the more significant of extreme climates. This reveals that the spatial distribution of extreme climate events will become more uneven in the future.

In this study, we first found that the few and sparse meteorological stations used in earlier comprehensive studies of building climate zoning in a complicated terrain area like Chongqing, China, may lead to the inapplicability of building energy efficiency standards in some areas. To address this issue, the study used daily data from 1908 extremely dense surface meteorological stations from 2011 to 2020 in Chongqing, China. In order to conduct fine zoning of building climate in Chongqing, China, GB50176-2016 and ASHRAE standard 169-2021 were employed, respectively. The findings indicated that by using the ASHRAE standard, the entire Chongqing region was classified into five climate zones. The Chongqing region was categorized into three different climate zones using China GB50176-2016: cold zone (CZ), hot summer and cold winter zone (HSCWZ), and mild zone (MZ). Not to be overlooked is the MZ (China’s GB50176-2016)/mixed-humid zone (ASHRAE standard), which is primarily situated at higher elevations in the southeast and northeast of Chongqing. In comparison to the HSCWZ/warm-humid zone, these zones have drastically different building energy efficiency regulations and approaches. According to preliminary projections, improved building climate zoning will to some extent increase building energy efficiency and reduce emissions in Chongqing. Finally, this study case can be replicated in different regions with complicated terrain.

Based on the projections of three shared socioeconomic pathways (SSPs) scenarios of three climate models of CMIP6, this study analyzed the standardized precipitation evapotranspiration index (SPEI) to understand the future meteorological dryness/wetness changes in the Poyang Lake basin (PLB) from 2021 to 2100. The effect of temperature change on the dryness and wetness variation was explored by comparing the trends of SPEI and standardized precipitation index (SPI) at multiple-time scales and different SSPs scenarios. The results indicate that the frequency of drought events may increase by 1.1~3.8% than the historical period in the three scenarios, and they may be higher than that of wetness events in the future of this century. Cumulative months of drought events are higher in most decades than the wetness events, and especially in the 2090s. A total of 43 months may suffer drought events in the 2090s under the SSP585 scenario, which is more than twice the wetness events. With the enhanced concentration of greenhouse gas (GHG) emissions, both the frequency of droughts and the proportion of extreme droughts show a significant increasing trend at 99% confidence in PLB. The spatial distribution of net precipitation is generally in the southwest–northeast pattern, yet it is still in different values in most scenarios; thus, the uncertainty of dryness/wetness spatial conditions should be considered. The SPI detects more wetness events and a more intensive wetting trend, while the SPEI shows the opposite. The difference between SPI and SPEI gradually increases with GHG emission concentration, and may even lead to contrary conclusion in the last two decades at a 48-month scale under the SSP245 and 585 scenarios, indicating the unneglectable impact of increasing temperature and evapotranspiration on the dryness/wetness conditions in the future. The research results can help to predict the evolution pattern of dry and wet occurrence in the PLB in the future and promote flood/drought control and disaster mitigation.

Extreme hourly precipitation is amongst the most prominent driving factors of flash floods and geological disasters. Based on the hourly precipitation data of 35 stations in the Three Gorges Reservoir Region (TGRR) from 1998 to 2020, we analyzed the spatiotemporal variation characteristics of hourly extreme precipitation indexes. The selected indicators included the frequency, intensity, period, annual maximum, trend of hourly heavy precipitation (20–50 mm/h) and hourly extreme heavy precipitation (≥50 mm/h) in the TGRR. Closely related climatic factors such as the Western Pacific Subtropical High Intensity (WPSHI) were also discussed. The results showed that in 2010–2020, the cumulative frequency of heavy precipitation magnitude between 25 and 40 mm/h slightly increased, while the corresponding frequency for magnitudes ≥50 mm/h decreased. In summer, the frequency of both heavy and extreme heavy precipitation increased in June and decreased in August, indicating a shift of extreme events to an earlier time in the flood season. The cumulative frequency of heavy precipitation in July had a period of about 7a, and that of extreme heavy precipitation had a period of 3a. The annual average intensity of heavy precipitation and extreme heavy precipitation in the TGRR was 28.9 mm/h and 61.4 mm/h per station, respectively, and both fluctuated and insignificantly decreased from 1998 to 2020. The annual maximum hourly precipitation center in the TGRR moved downstream from west to northeast. The frequency of heavy precipitation was relatively small along the main stream of the river valley. Both the frequency and total amount of heavy precipitation in southeast of the TGRR were significantly higher than those in other regions. Heavy precipitation in the majority of stations with high elevation (higher than 500 m) showed a decreasing trend. The cumulative frequency of precipitation with an intensity of 20–50 mm/h was closely correlated with the Western Hemisphere Warm Pool (WHWP) Index in February and the WPSHI Index in January, and especially, the abnormal large annual frequency (top 20%) showed strong correlation with the two indexes, implying highly predictable factors for extreme events. The frequency of precipitation intensity above 50 mm/h was correlated with the Western Pacific Warm Pool (WPWP) Area Index in January and the WPWP Intensity Index in November of last year. The research results provide a strong and refined factual basis for the assessment and prediction of extreme precipitation, and for disaster prevention and mitigation, in the TGRR.

Revealing the spatiotemporal patterns and controlling factors of atmospheric CO₂ in the Sichuan Basin (SCB) is a prerequisite for the scientific regulation of regional carbon sources and sinks. This study investigates surface and column-averaged CO₂ concentrations in SCB and surrounding regions during August to December 2024, using in situ measurements, Orbiting Carbon Observatory-3 (OCO-3) column-averaged CO₂ retrievals, and a Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulations and footprint analysis. At the national atmospheric background site JinFoShan (JFS), observed CO₂ concentrations rose from ~404 ppm in mid-August to around 440 ppm by late December. Comparisons between observations at JFS and WRF-Chem show that simulations driven by Open-source Data Inventory for Anthropogenic CO₂ (ODIAC) fossil fuel emissions and Vegetation-Global-Atmosphere-Soil (VEGAS) biosphere fluxes yield the highest Pearson correlation coefficient (r = 0.77). The diurnal and seasonal variabilities at JFS are primarily controlled by biospheric fluxes, with fossil fuel contributions weak in August to September and slightly enhanced in October to December, partly due to regional transport from downtown Chongqing revealed by footprint analysis. By contrast, Yongchuan station, closer to urban Chongqing, shows mean CO₂ levels ~10 ppm higher than JFS. For satellite observations, OCO-3 Snapshot Area Map (SAM) measurements over the SCB suffer from substantial missing samples and high spatial noise. We find no spatial correlation exists between SAM retrievals and simulations over Chongqing, and only weak positive correlations appear over Chengdu using ODIAC and Gridded Fossil Emissions Datasets (GridFEDs), whereas results based on the Multi-resolution Emission Inventory for China (MEIC) show no correlation, likely related to biased suburban emission spatial distributions. Overall, the spatial correlations between SAM retrievals and model simulations are weak, ranging from −0.22 to 0.31. To our knowledge, this is the first study to systematically compare in situ observations and OCO-3 SAM retrievals with WRF-Chem simulations in the Sichuan Basin.